Media and publishing
Newsrooms watch which stories are rising minute by minute and promote them on the homepage.
Count events as they happen, rank what is trending, and see which keys carry the load.
One counter per day. Each event is a single in-memory increment.
An animated walkthrough with real HotKV commands and example replies. Click any step to jump to it.
Dashboards that lag by minutes are not real time. Writing every page view to a database and aggregating later is expensive, and when one key suddenly takes most of the traffic, you often find out only after a node falls over.
Counters and sorted sets absorb a constant stream of events cheaply, and the totals are readable at any moment. Hot key detection shows which keys are hit hardest, and the engine's own metrics are exported in Prometheus format.
One counter per day. Each event is a single in-memory increment.
INCR pageviews:2026-10-16Sorted sets keep articles in order as views arrive.
ZINCRBY trending:articles 1 article:42The dashboard refreshes every second.
ZREVRANGE trending:articles 0 9 WITHSCORESWith hotkey-tracking enabled, the most accessed keys are listed without scanning.
HOTKEYS TOP 3Newsrooms watch which stories are rising minute by minute and promote them on the homepage.
Feature usage counters per day feed live dashboards without an event warehouse in the hot path.
Hot key detection points at the key behind a sudden CPU spike before it takes a node down.
INCR per event, per bucket.
INCRINCRBYSorted sets ordered as events arrive.
ZINCRBYZREVRANGEThe most accessed keys, approximate, without scanning.
HOTKEYS TOPThe engine's own metrics on a metrics port.
Put the bucket in the key name, such as pageviews:2026-10-16, and add an expiry so old buckets clean up.
Use HyperLogLog with PFADD and PFCOUNT. See the probabilistic counting use case.
Yes. HotKV exposes built-in metrics in the Prometheus format.
HotKV speaks the Redis protocol, so you can point an existing client at it and run these same commands.